|
|
Absolute deviation, 绝对离差* O1 h/ a0 ~& w( a9 ~! x
Absolute number, 绝对数( x) X9 o9 p% Q$ r4 k3 s
Absolute residuals, 绝对残差
: z j2 \, e7 U* T8 S7 DAcceleration array, 加速度立体阵
+ f$ @. | T J( [: {5 a% |Acceleration in an arbitrary direction, 任意方向上的加速度
3 \0 W# A8 l+ }" rAcceleration normal, 法向加速度- Z# @) e5 Y7 ]) a
Acceleration space dimension, 加速度空间的维数
/ \) l- w p0 f/ _6 o8 ^Acceleration tangential, 切向加速度. z" ^4 Z& q! C
Acceleration vector, 加速度向量
( G% n0 V1 v, v/ e: KAcceptable hypothesis, 可接受假设 v n: \( L( y6 r1 c& K- F
Accumulation, 累积5 ~& k4 y6 ?6 Q) J- x* v
Accuracy, 准确度
g, r; @9 M8 @5 v( b4 hActual frequency, 实际频数& s, y- g7 [* [
Adaptive estimator, 自适应估计量) |7 K5 S4 I; t- a
Addition, 相加* M8 R3 P* u9 U) Q; o; [$ ^+ d
Addition theorem, 加法定理+ a3 |4 ~1 K e' l
Additivity, 可加性
/ O% v5 B2 g3 j' i2 k$ B$ bAdjusted rate, 调整率' i. a* z( \+ [. C7 c
Adjusted value, 校正值
2 E1 }! F, b# Q8 z, {# q5 DAdmissible error, 容许误差
+ Y2 J( Q, e) W" o# QAggregation, 聚集性
: K. ^- Z* p I8 {$ {& TAlternative hypothesis, 备择假设
4 z/ j: e9 m5 k) M; u. aAmong groups, 组间 F9 U: ?' w: t
Amounts, 总量& J- E) Z, S8 _) A
Analysis of correlation, 相关分析
0 C; e& n- I# g' s8 |- RAnalysis of covariance, 协方差分析
( P- ~$ S+ x1 [; y0 \% ZAnalysis of regression, 回归分析2 _, e; ^" O. ~8 J1 w2 ?9 X
Analysis of time series, 时间序列分析
4 h' R6 F; m- ~. T3 y8 gAnalysis of variance, 方差分析5 O! n9 x1 Z5 n
Angular transformation, 角转换6 ~' }8 v" ?* |7 K% F4 o
ANOVA （analysis of variance）, 方差分析
( w. H, O& V9 h3 \ R. JANOVA Models, 方差分析模型: m D ?/ J9 A7 e- k* ]0 E" N1 b5 `
Arcing, 弧/弧旋0 n& F( n3 w, t: l
Arcsine transformation, 反正弦变换 u* W4 L! Q5 D. n9 o4 a3 s. Y0 R6 C
Area under the curve, 曲线面积
& ?+ k* B( d; w# F' ?" V- @; TAREG , 评估从一个时间点到下一个时间点回归相关时的误差
1 a. F" ^ g1 U. O0 m0 uARIMA, 季节和非季节性单变量模型的极大似然估计 , n p8 L- W+ ]- [8 y
Arithmetic grid paper, 算术格纸
5 J# R1 n6 m- ]& SArithmetic mean, 算术平均数- `, F* H+ c1 N
Arrhenius relation, 艾恩尼斯关系0 w$ J) s6 D1 \$ J1 r
Assessing fit, 拟合的评估% Z+ n$ ?+ [" Q. T) D' h
Associative laws, 结合律3 \8 d C2 m$ Q9 q8 E8 N: T
Asymmetric distribution, 非对称分布
2 C& I* ~6 X+ uAsymptotic bias, 渐近偏倚
( b$ u3 {4 d g1 W" zAsymptotic efficiency, 渐近效率' w/ k2 t0 z. j1 t
Asymptotic variance, 渐近方差
- Y9 H5 }, f2 j* \- }Attributable risk, 归因危险度
]2 X2 @" i* n+ a& B+ QAttribute data, 属性资料
+ {' |& Q7 b6 Y7 X* d% z& T" Q% j) oAttribution, 属性
/ i# F$ f6 J$ i! r/ T9 ^* VAutocorrelation, 自相关
8 y0 A0 |- A" i) ?4 w! g; VAutocorrelation of residuals, 残差的自相关1 E* d2 z; o4 e3 f) V. h. k. `
Average, 平均数/ [: T1 Z7 K! T) \# E
Average confidence interval length, 平均置信区间长度
# H( i+ N8 u7 H+ N3 mAverage growth rate, 平均增长率
+ L4 p, m, B7 R7 U, {Bar chart, 条形图
- }" w- P- y5 [! X6 r& V) }/ }Bar graph, 条形图
8 h. E- P7 b) ]% o! ^% U* kBase period, 基期7 {) F6 m+ M3 |, ^9 b
Bayes' theorem , Bayes定理* \5 s4 x) s A2 T. `8 H9 `
Bell-shaped curve, 钟形曲线
! p% J* H, [% A- z+ k5 q$ k% m( `Bernoulli distribution, 伯努力分布
+ c5 J4 Q" J4 ]2 s8 Y- dBest-trim estimator, 最好切尾估计量1 Z) i: S$ M, S: K/ O" {) B
Bias, 偏性* S- ~+ L2 R9 i% q
Binary logistic regression, 二元逻辑斯蒂回归
' |3 A1 s; R" d4 q( ?& LBinomial distribution, 二项分布% g& { l6 @5 [$ o
Bisquare, 双平方& _4 K6 v" Y( L3 m; O8 l" H
Bivariate Correlate, 二变量相关
' }6 g0 N$ I8 ~* SBivariate normal distribution, 双变量正态分布% [( P' P8 q3 `1 t: @
Bivariate normal population, 双变量正态总体 V$ D L, N- Z; u" D3 G
Biweight interval, 双权区间% S F2 G6 ^6 y
Biweight M-estimator, 双权M估计量
7 I. Q, m& H9 U/ Z2 R7 ?7 YBlock, 区组/配伍组 I3 p }1 M8 Z( q/ b8 [
BMDP(Biomedical computer programs), BMDP统计软件包
- u4 W& x5 ^; u4 w aBoxplots, 箱线图/箱尾图
7 X) h( l1 u/ ABreakdown bound, 崩溃界/崩溃点 U! @8 d7 h0 _9 K% z
Canonical correlation, 典型相关! M* {0 f: o4 B! v5 d
Caption, 纵标目# }) a8 K7 K& a; C$ N6 r# |# ^
Case-control study, 病例对照研究0 W* C* \* Y- v* e0 b7 c6 j
Categorical variable, 分类变量
" G3 n3 D8 W2 n' VCatenary, 悬链线
9 _& \4 r8 Z+ [4 Q( ?Cauchy distribution, 柯西分布
0 b3 d5 |+ v3 `5 OCause-and-effect relationship, 因果关系7 R& S v: L% w' z9 N/ d8 H) F$ f
Cell, 单元
# d0 q: j2 j6 Z1 X8 [Censoring, 终检
, `9 x0 [7 w& E l6 f! xCenter of symmetry, 对称中心
, `1 `6 o1 x3 v! ACentering and scaling, 中心化和定标
& K8 i4 k) Z6 J" PCentral tendency, 集中趋势# H. T8 |5 w! _ `' s: H% A
Central value, 中心值
- P% T# B" _4 TCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测5 t3 }- ] } M' g4 z/ \9 _
Chance, 机遇/ C5 x$ ?( ~" l% N" b& Q8 r) J
Chance error, 随机误差
0 k: Q0 q6 l. m) Z' \# oChance variable, 随机变量) U: m- f3 y& V4 v( c0 k% _
Characteristic equation, 特征方程
; _8 }9 C" ^! ?3 j; H6 b6 PCharacteristic root, 特征根
0 y4 M7 o: c7 ?; }: ~- OCharacteristic vector, 特征向量) \/ W& H# N4 a+ T+ e
Chebshev criterion of fit, 拟合的切比雪夫准则
V/ P0 `; ^6 t! sChernoff faces, 切尔诺夫脸谱图
# L3 L' X/ w, T+ l, R, u8 ^3 ]Chi-square test, 卡方检验/χ2检验
2 X. V2 d* X# |/ s1 f, GCholeskey decomposition, 乔洛斯基分解% ]4 R: ~& R6 y" K8 z& c- @
Circle chart, 圆图 : R0 k0 B4 n& R% ~; W; S
Class interval, 组距8 V4 J$ j+ y! g1 K& D
Class mid-value, 组中值% e$ T$ V4 \/ E8 @+ |7 R: O' Q4 {0 Q
Class upper limit, 组上限
9 z: p4 m8 _( VClassified variable, 分类变量! \5 U# G& {7 n4 T
Cluster analysis, 聚类分析
* Q' c: W4 { P3 l- d. C6 Z6 iCluster sampling, 整群抽样
1 W- ?+ C5 G3 t% K+ LCode, 代码
6 k5 Y. z9 T* q/ W3 @Coded data, 编码数据" a: H4 A/ H# V+ \- ?4 i7 M
Coding, 编码/ m# B0 p5 ~# B$ s9 W
Coefficient of contingency, 列联系数
) w+ k1 W5 b3 T" L3 j% D) T' GCoefficient of determination, 决定系数
$ p6 f/ M I! S3 gCoefficient of multiple correlation, 多重相关系数; D# O5 p) g" b0 h. z: @) O( G
Coefficient of partial correlation, 偏相关系数6 x! n0 _& z* d3 R. Y
Coefficient of production-moment correlation, 积差相关系数: G4 A. g) e( R7 i2 d
Coefficient of rank correlation, 等级相关系数
' u9 P( }1 S8 D0 @5 x$ yCoefficient of regression, 回归系数 n# r* ?) [! I6 M
Coefficient of skewness, 偏度系数5 [" x. s5 c3 q5 a l1 v
Coefficient of variation, 变异系数/ e8 E; T5 v- O9 h. x' w5 k, \
Cohort study, 队列研究# ]) w" r' g' K/ f7 X" p
Column, 列
- ]3 W; @( x! Y0 A9 g* J# R( w! XColumn effect, 列效应
% i! G& \ o7 o; {2 x2 VColumn factor, 列因素4 w5 j! n& J6 f- W$ n& D, _, b/ j+ q
Combination pool, 合并9 n# p H: [& U. [; Y' E) }' ~
Combinative table, 组合表
0 T/ e8 z d: a6 l1 ]4 sCommon factor, 共性因子- n3 W% a' ?$ D, A7 t
Common regression coefficient, 公共回归系数
, m5 f2 z0 R, u( S- iCommon value, 共同值 ^5 R2 {+ _) f% |. v- k8 J
Common variance, 公共方差
. J7 e- j8 g( I2 {" wCommon variation, 公共变异
$ S$ q1 B+ r! U" S9 |- UCommunality variance, 共性方差
: A2 V- Q: @/ F( I+ O7 i1 u2 lComparability, 可比性/ F- h0 f: h( u5 F% n9 C6 B
Comparison of bathes, 批比较
: G, `7 |8 [) S; p( @5 Y4 @Comparison value, 比较值
% s9 l5 D9 c K$ _Compartment model, 分部模型. Y. m1 ~: E: l" s5 c' C% i# [
Compassion, 伸缩+ ~& a, L, I+ x& W& o
Complement of an event, 补事件
; m5 e+ E! w' KComplete association, 完全正相关
1 s/ k% b0 e& o9 f' sComplete dissociation, 完全不相关
! o( V; v9 z* C- s1 r |$ C( b1 bComplete statistics, 完备统计量) v- c2 G. Y4 e
Completely randomized design, 完全随机化设计. C# k0 B* U7 e9 u r( C- ?
Composite event, 联合事件
6 i) Y+ h6 {0 s) V' D: u- ZComposite events, 复合事件( I! o1 m. j" u7 @
Concavity, 凹性" U2 L* b+ m0 Q
Conditional expectation, 条件期望+ p3 A; \) {- q% e
Conditional likelihood, 条件似然$ D# C) Q8 B/ u1 s: H$ N$ \% g# b
Conditional probability, 条件概率; T- m. r# S" L, e( L% J; F0 r
Conditionally linear, 依条件线性
4 ], ]+ i' N% g1 }% TConfidence interval, 置信区间0 ]6 F6 R+ D7 K" x
Confidence limit, 置信限
! C. t3 z. ~$ s: f, I9 M) ]2 UConfidence lower limit, 置信下限
( R$ U/ ?3 p; |# x4 }) ]" RConfidence upper limit, 置信上限
: c* Y2 M/ Q& x( G5 A7 rConfirmatory Factor Analysis , 验证性因子分析6 Y3 _* ?. v; Y; N
Confirmatory research, 证实性实验研究$ Y! C) W% D3 L9 E: N! V+ m
Confounding factor, 混杂因素! k+ d( Y9 J1 y% Z
Conjoint, 联合分析
! e+ B1 Q1 U1 `! i1 ^" @9 TConsistency, 相合性6 {% ]% N% p: c* Z6 ~4 i5 V8 W
Consistency check, 一致性检验
4 z* d* I( ^7 T) r0 {Consistent asymptotically normal estimate, 相合渐近正态估计
z% Z! Z: q" N; {8 h" GConsistent estimate, 相合估计& P# z! x( X5 I
Constrained nonlinear regression, 受约束非线性回归* I8 y2 L5 W1 I z! d& J$ f
Constraint, 约束& D8 m! M$ Q/ a/ h3 f3 z! q
Contaminated distribution, 污染分布% ?. ?( c- `9 D$ G$ u
Contaminated Gausssian, 污染高斯分布
; c, ~$ S% ]3 b- k# _6 i& L: cContaminated normal distribution, 污染正态分布/ f: n- y# s' s' N" @- e" C1 X
Contamination, 污染! P7 V( R2 N9 X8 g
Contamination model, 污染模型
' X( P+ Q- a( C( Q& p" DContingency table, 列联表
T8 O; r" W9 l0 P2 u qContour, 边界线. Z6 k' a* z/ U4 j/ Y/ s) _) ^2 M' U
Contribution rate, 贡献率
|5 Q& R( h5 L: k6 k, {Control, 对照
; F! E( I# D- }" n1 R% A6 Y3 d) pControlled experiments, 对照实验& G5 N, i S' L8 g& d% p" |
Conventional depth, 常规深度
4 w! V2 s' }5 X9 J2 _Convolution, 卷积
% V Q8 |$ X4 H8 l9 [Corrected factor, 校正因子) P) b/ d9 ~9 l- F9 l" ^! `$ x
Corrected mean, 校正均值
& J/ q; m D8 N3 I6 ACorrection coefficient, 校正系数
- v8 e% o' C9 G$ O E, k+ i, G: iCorrectness, 正确性
c- B8 I% B! a. b3 v1 I, I( KCorrelation coefficient, 相关系数! Y5 K( Q* n0 Q; s0 D0 a
Correlation index, 相关指数
6 x% ~4 E3 u% M& PCorrespondence, 对应
7 s) p* q( @2 T0 c( {Counting, 计数
& @$ f* u) t$ U# r: |6 _- vCounts, 计数/频数
9 X8 ^- P# j1 ]# Y0 {7 zCovariance, 协方差
( l; R$ }! \- ^. pCovariant, 共变 6 ?) C2 Y% K* G; y: E
Cox Regression, Cox回归
' P. L" S Z3 s ]0 B: @Criteria for fitting, 拟合准则
% `; s$ I4 {8 O; h4 a$ HCriteria of least squares, 最小二乘准则
6 q% j) L2 K, T3 h% W/ d! lCritical ratio, 临界比
& j$ x# J8 g- ?: l) I, A X& _Critical region, 拒绝域
$ n7 n0 {5 U$ \' t/ O2 JCritical value, 临界值
( M1 T- Q, R7 e% n) n0 m( ACross-over design, 交叉设计
+ C4 ~& ?7 v3 B) ^$ G* qCross-section analysis, 横断面分析
3 W* c) a* }5 Z- ?8 |1 S( eCross-section survey, 横断面调查4 f6 g. n# g& b. {0 P" O" w
Crosstabs , 交叉表
1 n/ ^ m# K0 ~4 K; U( C/ G/ PCross-tabulation table, 复合表
; b6 n) j6 O( S3 b! `# W6 ]Cube root, 立方根8 K1 I8 v+ s# {( {7 x: c: r E: y
Cumulative distribution function, 分布函数
4 S2 O) S( E. s* Q0 b0 d2 aCumulative probability, 累计概率3 N6 p3 B3 M2 v
Curvature, 曲率/弯曲2 V( \1 I8 U+ a5 p+ H, Y2 ?* f, Z7 N
Curvature, 曲率
4 Q1 y z" O+ x8 |! T: P. eCurve fit , 曲线拟和
+ ^) ?, H' i# V) I1 @Curve fitting, 曲线拟合, T r4 Y4 Z& g9 b' B4 ?
Curvilinear regression, 曲线回归
* n' ]9 [2 z5 _, F+ B0 o" | kCurvilinear relation, 曲线关系
, n" h3 L% [% K# M, FCut-and-try method, 尝试法
% |- h6 u! N: Q$ I$ m6 B TCycle, 周期. m: d" A# G6 `5 w0 p/ p
Cyclist, 周期性
: L2 d6 s- [& U/ e( iD test, D检验
6 z7 i+ z3 w' A) w5 sData acquisition, 资料收集" ~8 ^9 S) x& P& C5 T6 d: N W
Data bank, 数据库+ ^0 h3 d1 l0 G% {
Data capacity, 数据容量
: T) h6 k# a2 w; m/ A8 dData deficiencies, 数据缺乏
1 q( U0 V+ t/ N$ pData handling, 数据处理
! ^# s3 t% j4 |/ z9 k9 i! z- HData manipulation, 数据处理1 y" C6 g* n# A. h% l
Data processing, 数据处理
2 h) } T& s7 w* q% KData reduction, 数据缩减
8 j% {& H8 U) U" g% m8 k+ W6 o7 e5 KData set, 数据集
. z; D3 J2 |4 O$ D' J/ x; YData sources, 数据来源
! a! c7 F9 J' H& ]Data transformation, 数据变换
2 m( k2 D7 ~6 i/ m+ VData validity, 数据有效性
' w1 b1 M; e0 ^% W! C" ~ fData-in, 数据输入
: Z( w1 i: ~) m m- X/ LData-out, 数据输出
4 _& ?+ n0 W/ Z1 o9 h, W! \Dead time, 停滞期- u# } r5 H# E
Degree of freedom, 自由度
: u2 z+ _3 p) d/ h& kDegree of precision, 精密度
- }7 y; E' {& ?Degree of reliability, 可靠性程度
0 M. c8 B& ]( }' a7 h9 a4 ?Degression, 递减/ Z9 j$ |% z3 ^; S/ F" ?
Density function, 密度函数
, k; c( ` M) M, l xDensity of data points, 数据点的密度& a. i3 b. g; ~. K/ y
Dependent variable, 应变量/依变量/因变量
0 P8 F8 q# B; E1 W. m sDependent variable, 因变量3 Q+ ^- ^5 L# L V
Depth, 深度
9 O% e9 c' [5 f* YDerivative matrix, 导数矩阵
e8 R' O4 E2 ^# W/ Y8 K( h: A2 SDerivative-free methods, 无导数方法
8 z6 I0 G$ z- d1 {8 W dDesign, 设计6 ^ _6 @4 J) U) }* z) p b
Determinacy, 确定性# S/ T, z) _, S; \. |/ w6 T% m
Determinant, 行列式/ f; o& E+ X1 h+ a K7 G: P
Determinant, 决定因素5 u: I- S! j" s3 y4 s- y! s
Deviation, 离差
6 O) Y" @" X7 UDeviation from average, 离均差
Y. F, @7 F: mDiagnostic plot, 诊断图 f( y: {8 x: p/ E
Dichotomous variable, 二分变量
e9 v+ ?6 r1 }Differential equation, 微分方程& U$ i6 y9 H5 r1 G" s
Direct standardization, 直接标准化法
; j8 P% [' g5 I: Q# r5 b2 ]Discrete variable, 离散型变量( M8 Q4 {4 q% Z* G- G" O
DISCRIMINANT, 判断 % h6 x7 j4 {5 z4 d, U9 u
Discriminant analysis, 判别分析3 J6 i7 d& L6 U6 k- G
Discriminant coefficient, 判别系数
/ e+ V8 i" |8 D+ F" G3 SDiscriminant function, 判别值% {' Q6 O/ c; v
Dispersion, 散布/分散度0 w: ~7 C& F8 e i B+ b9 W% D- `" H
Disproportional, 不成比例的6 I9 T& A1 }$ K5 v) o! F
Disproportionate sub-class numbers, 不成比例次级组含量1 |" g$ q; R8 D) { n
Distribution free, 分布无关性/免分布' R# Y, b# v) l3 Q y/ ~' X
Distribution shape, 分布形状# }. S6 e/ h: ~2 m
Distribution-free method, 任意分布法
% ]' i I9 x- d5 Q# l0 u7 b( GDistributive laws, 分配律
8 ^; E( ~! q- eDisturbance, 随机扰动项3 P$ _3 a8 P! @) W4 o; m
Dose response curve, 剂量反应曲线0 \3 n% Y# g# m" D- A2 N* C% c4 z* z5 o
Double blind method, 双盲法 C; A, z+ `9 h
Double blind trial, 双盲试验0 l( }( I1 ?- a9 }
Double exponential distribution, 双指数分布
o; Y. x! G' c8 _& U* _7 ~4 `Double logarithmic, 双对数& h' X* p6 J9 L( u; k' O' h8 O/ D
Downward rank, 降秩+ i! u5 A) `5 v: {8 D
Dual-space plot, 对偶空间图! ?5 ]0 t8 L! U0 O6 [9 J
DUD, 无导数方法( C7 P' w" ?1 z$ e! k8 c0 O
Duncan's new multiple range method, 新复极差法/Duncan新法
: Q! e0 @; z3 B5 g) YEffect, 实验效应
/ \# A/ F2 l6 ~1 z1 PEigenvalue, 特征值! H+ Q0 a! r$ q9 @
Eigenvector, 特征向量6 W4 m3 X5 \, Y& f1 G( |
Ellipse, 椭圆 u2 c" P/ u8 \# y/ H$ {3 y
Empirical distribution, 经验分布
9 Z. g, I( e/ c' R. REmpirical probability, 经验概率单位
8 L2 z; H2 u& U4 M% j; Z6 ]Enumeration data, 计数资料
4 @$ O0 P+ O3 K/ ?2 j4 e0 oEqual sun-class number, 相等次级组含量
6 n. D7 f: z5 e! n( R; F2 qEqually likely, 等可能+ K, I' Z( b- X s2 A5 G
Equivariance, 同变性( J; Q4 l5 x1 L5 E# T ` W* K( ]6 l
Error, 误差/错误
U; }5 r G5 J+ e& JError of estimate, 估计误差, w7 P- H2 u. Y X' l: N }
Error type I, 第一类错误' u. ?0 {3 G" {
Error type II, 第二类错误! f% j3 \& t* x9 d1 F
Estimand, 被估量' r- v5 \4 R1 W+ z) ~( i8 y- `
Estimated error mean squares, 估计误差均方% [; l& u e& C) C3 n; F. w
Estimated error sum of squares, 估计误差平方和
# Y# C& M5 V; u0 V" `Euclidean distance, 欧式距离
K2 D9 A" Z% Q }! O- q/ t" M" OEvent, 事件
) B% B1 |& A' [4 B& b7 CEvent, 事件. N/ p: O$ L; C8 E u
Exceptional data point, 异常数据点) s( I7 `$ I8 L& _/ O z- `9 x
Expectation plane, 期望平面
0 w; x' d% F5 x* V" qExpectation surface, 期望曲面9 N! [3 V- ]5 S+ e# m
Expected values, 期望值
/ X4 \# S+ M4 v$ f3 {8 \) C1 uExperiment, 实验
, W& h3 h% M* r# r' hExperimental sampling, 试验抽样: i& I# _, U1 o% k8 [) _$ p
Experimental unit, 试验单位/ O* U! {! W/ l
Explanatory variable, 说明变量
. x4 w$ `: {7 X# |- _4 [6 MExploratory data analysis, 探索性数据分析' {6 @) a! a ?! F& N* S
Explore Summarize, 探索-摘要. N! t3 O9 T9 X- K
Exponential curve, 指数曲线8 B1 C7 u. U0 a4 ]! j; A
Exponential growth, 指数式增长
7 n) G% \* k; o; z8 A+ q5 LEXSMOOTH, 指数平滑方法
' D, m0 U2 M6 \. l+ K0 x' a; ^9 ZExtended fit, 扩充拟合, u* i7 s: ]/ h% q* E/ }
Extra parameter, 附加参数
$ U3 l3 Q/ E q# ^) E7 s* D8 z, }Extrapolation, 外推法
* h4 g. P' Y# N0 I& k2 S3 e% HExtreme observation, 末端观测值+ D7 t8 j0 {0 k- O
Extremes, 极端值/极值2 O) ]& @2 N2 L- q6 ]1 ?: ~. R
F distribution, F分布
5 L3 q4 ~4 U- d) ~* R; I* O5 X ^F test, F检验
+ `% ~6 K) N. b$ f' {! T& @8 OFactor, 因素/因子8 t" P6 N; B4 i
Factor analysis, 因子分析' \ x; B4 h9 v* k! `+ C) p
Factor Analysis, 因子分析, D: V% I5 p! R$ d+ n# s
Factor score, 因子得分
1 c0 f p' D* L* KFactorial, 阶乘
# W# w- h' y: L" _, m* w0 A+ WFactorial design, 析因试验设计+ ]7 \, ~2 r. O- Z/ M7 \' n
False negative, 假阴性0 E a! ~3 }% n0 s' |' \
False negative error, 假阴性错误9 }0 W8 V/ a: c* `. F* m- W
Family of distributions, 分布族
: m. D+ ?9 }6 ?" i) O. W: gFamily of estimators, 估计量族
5 h. K3 o1 z+ D* _: AFanning, 扇面
6 x% R) K/ J4 S. HFatality rate, 病死率
3 g* d: b) \/ i9 CField investigation, 现场调查
1 k3 j" X5 H- Y2 M! |Field survey, 现场调查3 u, P$ l4 ~6 S* v# @; h0 \
Finite population, 有限总体! H7 j, D! O! [+ a' T5 l4 @
Finite-sample, 有限样本. b1 u* R6 P! I, u4 n' y% a
First derivative, 一阶导数1 z! x# n% P' U M+ f/ X
First principal component, 第一主成分, p) g+ N6 i- C
First quartile, 第一四分位数
[- X3 i7 d4 r1 xFisher information, 费雪信息量. q1 ~6 E5 ?4 U/ K4 b& m
Fitted value, 拟合值
0 t; z1 ]& {8 t1 K, \+ ^, qFitting a curve, 曲线拟合$ b! ~5 R4 k; M% g9 O0 f! `" r
Fixed base, 定基# J6 ^ k' q; m
Fluctuation, 随机起伏
. Z' N+ h* F& j* bForecast, 预测* X1 Z8 Z2 H+ m+ e
Four fold table, 四格表$ T+ L& m! q. u6 H: [% T9 ]5 T
Fourth, 四分点
# q' _# ~; j' M7 ~Fraction blow, 左侧比率
Q# O p# \- }Fractional error, 相对误差
- ^; ]( m) l, P8 Q/ Y7 RFrequency, 频率5 x# O, H1 v6 j+ N5 ^' {/ D3 p# P6 d
Frequency polygon, 频数多边图
% Y5 F" X) \. `" m; v( ^6 P& D+ s! ]Frontier point, 界限点$ s9 } a: x$ R& s" N: U( N
Function relationship, 泛函关系( p, c) X! v$ I7 \ {
Gamma distribution, 伽玛分布
% B/ u4 V; n9 u2 S- j B, B: OGauss increment, 高斯增量" m$ G$ G# B/ q
Gaussian distribution, 高斯分布/正态分布3 a) K- }+ @# m4 M* G' e
Gauss-Newton increment, 高斯-牛顿增量
$ b \; j0 ^. b C( i; TGeneral census, 全面普查; E2 D3 t* j% l+ {6 @6 L4 u9 z) z
GENLOG (Generalized liner models), 广义线性模型
9 O/ @! X9 h. `# U( QGeometric mean, 几何平均数, z7 K7 V" I5 J w! ^9 X; {
Gini's mean difference, 基尼均差
. x# X* ^# I6 i4 t& g$ v( cGLM (General liner models), 一般线性模型
$ N* j- ~5 \9 H/ G6 ?Goodness of fit, 拟和优度/配合度
2 }4 J' X& h! u9 v# ]& B" [Gradient of determinant, 行列式的梯度 x5 e' I! P, j! t9 L
Graeco-Latin square, 希腊拉丁方! m% I4 |" h N. T
Grand mean, 总均值
- f8 I5 k; N" cGross errors, 重大错误1 a; Q8 o( L6 W: D
Gross-error sensitivity, 大错敏感度& }+ X3 X( g3 u: O
Group averages, 分组平均" n+ ?& j: S. R0 T" }$ a9 p5 q8 N
Grouped data, 分组资料" `" d' D/ y+ \! U% L! e8 T
Guessed mean, 假定平均数
+ P' C- h& o6 y8 u/ DHalf-life, 半衰期
: m9 Q; v2 L) G* k- P! ]Hampel M-estimators, 汉佩尔M估计量
+ x5 e" `& i$ j: l. |5 eHappenstance, 偶然事件
2 N3 t8 `8 v6 F- [$ q* }' B9 Y# xHarmonic mean, 调和均数5 y$ S& I6 F+ U
Hazard function, 风险均数
5 b4 O& e" h( C( n5 Z5 I# eHazard rate, 风险率
7 c* M% x& g7 M* I# _' {+ v6 D' ZHeading, 标目 5 I4 v5 `! ?9 B$ t$ s1 J
Heavy-tailed distribution, 重尾分布
$ Z2 B' l) E2 A8 P8 f& q0 W( z# {Hessian array, 海森立体阵) d# s, b; y, m2 l! ?# N
Heterogeneity, 不同质
% P& [8 Z+ }# g- sHeterogeneity of variance, 方差不齐
) o4 ]' q, O e: ?, a" G8 X R5 @Hierarchical classification, 组内分组" u9 j5 K" d4 E
Hierarchical clustering method, 系统聚类法
: F* G* {; R8 e, WHigh-leverage point, 高杠杆率点
" z* ?: |* |; eHILOGLINEAR, 多维列联表的层次对数线性模型# x* S+ x: E5 [% I5 r2 e4 S
Hinge, 折叶点
4 g! I. F& {% [+ |Histogram, 直方图
- B3 Z* M a7 o) UHistorical cohort study, 历史性队列研究
5 W. s3 R- s- s( N6 H3 D! iHoles, 空洞
" F3 ?$ ~' ]5 B& ]9 P# KHOMALS, 多重响应分析
& _" ~/ ~ z3 w& P9 \0 F* k5 A) G3 AHomogeneity of variance, 方差齐性
* ~5 x$ w: z) M& j: y3 ]5 ZHomogeneity test, 齐性检验
* O0 s4 F) |* RHuber M-estimators, 休伯M估计量4 ^5 J: b3 Y) X) O! U
Hyperbola, 双曲线
7 S0 u+ s! ~; w6 J# r0 \' `7 y9 fHypothesis testing, 假设检验
, ]) K( l& h, S( l; Y: F' EHypothetical universe, 假设总体
! z, o) y# ^3 z+ Z- c6 Z: B* nImpossible event, 不可能事件/ I( y6 S* x( \: t9 g
Independence, 独立性2 v/ ]. W6 U( Z7 w9 o4 Y( y
Independent variable, 自变量1 v2 T2 W& U S1 G$ r
Index, 指标/指数
% F2 ?* I) r" iIndirect standardization, 间接标准化法
5 D$ j: P- B6 d3 c3 ~Individual, 个体
5 J0 ?3 x& l; @6 nInference band, 推断带* F9 I7 B+ G6 i8 T& w
Infinite population, 无限总体' D, D4 o8 b6 J% N) R5 ^" A
Infinitely great, 无穷大. W) J9 Y6 Q" _) G
Infinitely small, 无穷小4 y% i7 ~' M6 \( u. X2 S$ D
Influence curve, 影响曲线8 w, z5 M1 x T& p9 J. R) ~
Information capacity, 信息容量
$ \5 r: E ?' r! p8 A4 gInitial condition, 初始条件+ m5 W2 {$ {- t1 c7 |: x% ?
Initial estimate, 初始估计值
1 h: X0 S8 [2 Q% N) g% v2 M, ^Initial level, 最初水平: h& ]' Z3 M3 U; _% Y- B
Interaction, 交互作用
0 A: s3 s$ F5 U" @: s8 MInteraction terms, 交互作用项
( s, r" z2 j' i5 K; S6 }+ D$ `Intercept, 截距$ i9 P* F$ T: [' o- {5 c
Interpolation, 内插法
1 I3 _& r# Z& E' DInterquartile range, 四分位距
, N$ P. Q6 H* ^$ r) v8 ~/ U1 pInterval estimation, 区间估计
) F" k" e6 c2 H4 aIntervals of equal probability, 等概率区间
" a! {$ E* d8 ]# E3 W O7 m- UIntrinsic curvature, 固有曲率3 c! h6 H6 D4 \( y+ q
Invariance, 不变性5 Q# M7 k& y# c+ |
Inverse matrix, 逆矩阵
7 E9 q& K' V' RInverse probability, 逆概率; f1 A/ s: p8 X; [3 S
Inverse sine transformation, 反正弦变换
& t% E/ ?, O( o0 \: B( H9 h" dIteration, 迭代 1 ^2 x* o+ F( `/ e# ]
Jacobian determinant, 雅可比行列式# ?+ C# {8 P: h8 M3 n9 T
Joint distribution function, 分布函数2 i8 t0 D m2 P( F3 p1 K
Joint probability, 联合概率9 ?% C0 c# S4 o* C: {0 o7 w
Joint probability distribution, 联合概率分布' L/ ]& g* l( m9 F1 a
K means method, 逐步聚类法
% D5 Q4 H$ s. Z& vKaplan-Meier, 评估事件的时间长度
5 l$ n9 V. I5 Y3 |Kaplan-Merier chart, Kaplan-Merier图* n3 o4 v+ k, n7 n% w `4 {
Kendall's rank correlation, Kendall等级相关
# k/ [" v: l7 U* c* VKinetic, 动力学
: ~' n$ H' d0 W1 tKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
* o2 v9 S+ |' v" HKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验+ T4 V# Q* D/ p9 C2 |" s) c5 M6 p' m
Kurtosis, 峰度( J2 i5 O7 ~1 G$ }; z: a
Lack of fit, 失拟
8 @1 f& i* B# u5 N) K! S+ Y2 ^Ladder of powers, 幂阶梯
* @6 N5 |) j4 X6 K, bLag, 滞后
/ T$ `, p; c6 N2 F! D4 @6 x1 x o* {! ~Large sample, 大样本
& |; G# S& p$ }5 S3 ELarge sample test, 大样本检验
9 c1 j4 r& E) |; k% [, l) z4 B( sLatin square, 拉丁方
$ p& D/ T& v# Y# j: qLatin square design, 拉丁方设计$ ]6 j* v7 |8 I3 \
Leakage, 泄漏
0 Z$ g/ q$ S+ ~9 l2 ?) FLeast favorable configuration, 最不利构形
- ~! z6 b4 c) S9 ]9 U! l. i6 O6 ~' ZLeast favorable distribution, 最不利分布6 y+ e4 S. { r; s4 y
Least significant difference, 最小显著差法
1 h* L: e7 H7 u: U5 Y8 z6 _Least square method, 最小二乘法! T0 _$ i+ N' q+ G% f
Least-absolute-residuals estimates, 最小绝对残差估计: G4 O% _* H- B3 Q5 ~4 V
Least-absolute-residuals fit, 最小绝对残差拟合
6 P) M7 R* g+ \1 h A& n" dLeast-absolute-residuals line, 最小绝对残差线
2 H; g4 C9 [1 L' M7 E( HLegend, 图例
& K8 \0 V' { p5 S& G+ Q. k2 m) `L-estimator, L估计量/ _$ r8 ]8 _/ k5 f3 {( ~
L-estimator of location, 位置L估计量- m5 _, F- m2 s @
L-estimator of scale, 尺度L估计量5 v- P, B# C. A' e" w
Level, 水平! W% r/ g) L/ \# V8 s. [
Life expectance, 预期期望寿命$ w( n" R" z1 ^3 y( O j
Life table, 寿命表" S2 \' w j' z* Q5 p0 V- b
Life table method, 生命表法
5 @. v2 a% i* X$ j7 U8 X' L5 zLight-tailed distribution, 轻尾分布1 w7 B% T% a' t
Likelihood function, 似然函数* c( `. Q$ Z, N; \
Likelihood ratio, 似然比3 `$ s1 m' R! J' ]" K' U# m; x
line graph, 线图
4 ]5 c* c k' R& s9 l' OLinear correlation, 直线相关3 |1 d/ x" @+ o' W8 _1 s: o
Linear equation, 线性方程4 T5 U; w1 q0 `: z" V, W4 j4 w
Linear programming, 线性规划& }, F" d; r& j2 n6 G
Linear regression, 直线回归
* K3 b0 K8 [' P5 KLinear Regression, 线性回归
0 H* W7 \ q! ILinear trend, 线性趋势
2 b: _4 E, X8 h9 V2 W8 i3 _, [Loading, 载荷
9 z+ H( o$ y* a( c9 }( @Location and scale equivariance, 位置尺度同变性& i/ D" h" C# M
Location equivariance, 位置同变性4 Z, h9 ]" v1 c+ f9 z9 U' l! d
Location invariance, 位置不变性9 m) A8 G1 s# c4 F- `/ D( L2 F
Location scale family, 位置尺度族
0 M8 B, c5 `( E. | {Log rank test, 时序检验
2 _% k) k( z& V6 P1 ? Y2 }/ b) s' KLogarithmic curve, 对数曲线+ ^! \. {7 M& k5 U+ `
Logarithmic normal distribution, 对数正态分布1 v2 A4 G& K. w, ^# u
Logarithmic scale, 对数尺度- y& P' v/ u; x( S t+ q9 k8 Q
Logarithmic transformation, 对数变换
) J0 A& e6 f% S& WLogic check, 逻辑检查1 `. i( f3 k$ z3 A* ~! o
Logistic distribution, 逻辑斯特分布4 L, C! p, ~- v- v6 K
Logit transformation, Logit转换& f( V' U0 p! U6 Q4 w
LOGLINEAR, 多维列联表通用模型
* |, G" H- [4 o/ h2 ZLognormal distribution, 对数正态分布
0 i1 ~5 W% Y( A1 C0 x4 R* S( CLost function, 损失函数
7 d2 x9 h, Z4 |' HLow correlation, 低度相关; u! w" m S) z) F& `' \# F% p5 g
Lower limit, 下限 E( h- c4 i; l' S% u7 c( ?
Lowest-attained variance, 最小可达方差: D! d! T) r) @9 j5 U$ @; h
LSD, 最小显著差法的简称* O r7 I) k1 M5 |) v
Lurking variable, 潜在变量
* F$ s$ Q" q9 [) ?2 WMain effect, 主效应7 ^& o. `5 W% d- j, S9 q3 i
Major heading, 主辞标目
/ \" n: g1 u. x% `2 S& G( oMarginal density function, 边缘密度函数$ e+ t( ~- ~3 U. W s3 ~
Marginal probability, 边缘概率
8 v4 |, f* V: m2 _+ s4 sMarginal probability distribution, 边缘概率分布, D( f3 G, [5 }# C( t
Matched data, 配对资料5 S& G8 b% z* Q; x/ K4 Y8 c( H
Matched distribution, 匹配过分布% M# K4 n6 Y5 [* a3 i$ ]% @
Matching of distribution, 分布的匹配6 b4 q1 [! p4 u3 h+ ^4 Q
Matching of transformation, 变换的匹配# l# u6 A% A3 e/ K' z
Mathematical expectation, 数学期望( m3 t, a8 }1 E3 d) ~( n1 S
Mathematical model, 数学模型
( ]+ F/ _0 O( j' MMaximum L-estimator, 极大极小L 估计量6 w! o3 y1 s* @! U
Maximum likelihood method, 最大似然法- ~/ v# g/ n! _/ A, s# b- e- k1 x# {
Mean, 均数/ |0 F$ p9 t6 r% W
Mean squares between groups, 组间均方( `; {* R. R" E6 ^% c7 o) I2 m; B
Mean squares within group, 组内均方
' P, ]9 R7 l7 ]" x& |# h6 o/ \3 _Means (Compare means), 均值-均值比较
/ m4 l. z1 G$ d8 H1 \: ]4 H; i6 _Median, 中位数
3 k) A8 ]7 a2 e4 j sMedian effective dose, 半数效量+ [0 E% N: [1 R% D
Median lethal dose, 半数致死量! m! }1 @- g( F z& j
Median polish, 中位数平滑2 y1 i8 v$ U% a' A4 N* ^
Median test, 中位数检验8 A9 n$ q0 T7 Z+ }- Y
Minimal sufficient statistic, 最小充分统计量
- a4 i' F3 H$ e/ RMinimum distance estimation, 最小距离估计& X: f3 S" z' _- Z/ I: v# s2 H' @
Minimum effective dose, 最小有效量9 ]$ B' L- E; H) I5 s
Minimum lethal dose, 最小致死量+ f* P1 G5 [! o8 t, g4 l9 q
Minimum variance estimator, 最小方差估计量, P! j6 {( R5 q& R# u# P u
MINITAB, 统计软件包& d! ~( p2 ?% d4 k
Minor heading, 宾词标目
* a& ^' X! u; W7 d1 IMissing data, 缺失值4 x9 ]% u: K7 u2 m4 C
Model specification, 模型的确定
" N! a0 S2 h2 c5 Z5 U zModeling Statistics , 模型统计
4 e j( ~! O( U+ D+ m, tModels for outliers, 离群值模型1 h1 @3 B2 G' N6 T2 j2 n
Modifying the model, 模型的修正; q5 w/ C" `6 {" E
Modulus of continuity, 连续性模1 g# g# o, l+ L K0 }. T" m
Morbidity, 发病率
5 n5 Q) o4 M' p" ?1 Q0 @% CMost favorable configuration, 最有利构形6 z J6 @/ C+ P. j, g! M/ B
Multidimensional Scaling (ASCAL), 多维尺度/多维标度0 ~" A! |! h8 P% W& b. T
Multinomial Logistic Regression , 多项逻辑斯蒂回归* m: k5 o; i' W
Multiple comparison, 多重比较
3 z. Z& I- w& h+ W& Z. ?Multiple correlation , 复相关
- E. V) J, ^0 n; {+ x1 @3 _Multiple covariance, 多元协方差
3 ^! u! V8 J1 U4 ~7 t# OMultiple linear regression, 多元线性回归* N$ b3 ^* n: g6 A) L& X
Multiple response , 多重选项9 m# Q+ F; y8 ~7 Z9 D: c
Multiple solutions, 多解, w9 i( x n+ H0 |6 r- }
Multiplication theorem, 乘法定理
( R ~* ~+ b' H8 M1 r, _. CMultiresponse, 多元响应
5 n* V' w- R8 a/ o# CMulti-stage sampling, 多阶段抽样
7 ~2 I7 c2 d, H% YMultivariate T distribution, 多元T分布! C* \2 c& o7 i4 P
Mutual exclusive, 互不相容
- ]" b: }4 H) h5 eMutual independence, 互相独立
$ Z$ B6 ~5 q+ [! O: Q& Z" J9 B7 q! B& ^Natural boundary, 自然边界
. `% q$ A# N. ~, K6 lNatural dead, 自然死亡" y$ w Z' `, R- F8 m) F
Natural zero, 自然零
) _4 I# u7 ] i- ~1 Z* ~! n3 U; KNegative correlation, 负相关 i! k8 K0 C8 A# `, _/ S/ h: G
Negative linear correlation, 负线性相关
2 S3 p5 m6 p, qNegatively skewed, 负偏
/ V J4 ^8 _$ U/ H8 i4 k2 t3 }Newman-Keuls method, q检验3 _# V1 Y" h' y! y; R! r, h' r
NK method, q检验& f/ I2 t+ k B% x: X# Y2 Y
No statistical significance, 无统计意义
0 A3 k+ G3 e0 s$ q( n( P' ?Nominal variable, 名义变量* ^$ c6 n5 |: H1 Q" B0 \' N1 Q
Nonconstancy of variability, 变异的非定常性
8 ^% W1 p l) m8 Q( iNonlinear regression, 非线性相关
) S5 o. j2 w3 G2 O+ l& X# h1 |Nonparametric statistics, 非参数统计/ K& Z1 R' a8 n: i. |" u
Nonparametric test, 非参数检验1 R; N8 ?( p* H r, Z* y
Nonparametric tests, 非参数检验
1 Q$ u' @$ V8 y9 J) y& I7 DNormal deviate, 正态离差6 l' g1 H/ M: W# y: _! G
Normal distribution, 正态分布8 R4 Q2 _$ A1 Y
Normal equation, 正规方程组! U! a& u" j& ^- Y6 i' I3 s' S
Normal ranges, 正常范围) Y* P7 a% g8 U0 ~; X
Normal value, 正常值- J& L3 h# C; u& o& s0 e- F0 V
Nuisance parameter, 多余参数/讨厌参数
6 u3 A" S! W+ T# h2 B3 jNull hypothesis, 无效假设 " T2 g: A3 [! ~, ^: m- c
Numerical variable, 数值变量
$ N8 d9 d. t x Q" QObjective function, 目标函数
3 I% z5 d6 l' w: \+ mObservation unit, 观察单位
$ i; C0 [0 O: H$ `( fObserved value, 观察值. o' e7 C, H- C/ _% Y2 x
One sided test, 单侧检验
3 Y7 N$ i @& cOne-way analysis of variance, 单因素方差分析/ k0 M' _7 ^1 ^ W0 {$ y
Oneway ANOVA , 单因素方差分析
2 ]3 y1 a! k. H4 I8 F. fOpen sequential trial, 开放型序贯设计8 W/ U; `/ o& o/ \
Optrim, 优切尾: U4 t2 t Y3 @
Optrim efficiency, 优切尾效率
$ J- ]% @9 y2 E+ t9 |; G7 a: w+ VOrder statistics, 顺序统计量! {* C0 M9 [& ?% u- W- G! Z, s% `
Ordered categories, 有序分类, \$ H; F( c/ Z* V. ?- a! s5 P
Ordinal logistic regression , 序数逻辑斯蒂回归' n6 a0 m5 ^6 b
Ordinal variable, 有序变量
+ m9 i* F) [8 \9 N3 h- v! R2 fOrthogonal basis, 正交基
g z2 S2 c* N& @3 _4 Q! M, lOrthogonal design, 正交试验设计
- G0 ^1 M" f" C z$ `Orthogonality conditions, 正交条件
/ y- y- ]! t4 m# A* jORTHOPLAN, 正交设计 7 H0 A" G1 p+ r- C' N8 q
Outlier cutoffs, 离群值截断点
0 R. F3 ~6 I7 BOutliers, 极端值2 u$ [/ A0 v2 O5 g( @
OVERALS , 多组变量的非线性正规相关
8 F: m* s/ u& |, e6 K( }1 W& oOvershoot, 迭代过度2 M+ [" u+ ^ E( w- D
Paired design, 配对设计% X. y6 x+ b( b8 p e% O' q; o7 p
Paired sample, 配对样本$ Q) T4 C2 ?2 P! |+ H
Pairwise slopes, 成对斜率
* [3 d- f8 U! @# V* ?) {2 I/ f ZParabola, 抛物线. P; V/ W* q8 s' a+ {
Parallel tests, 平行试验
) K) @7 X( `3 P6 UParameter, 参数
5 w# o9 y- X0 S6 OParametric statistics, 参数统计
9 X* r3 y/ T# }# T6 |/ CParametric test, 参数检验1 o" n0 O& a. I6 b/ X9 ~ [
Partial correlation, 偏相关
# l$ v6 C6 V3 z( U6 WPartial regression, 偏回归% ]/ K1 {( H; J$ ^1 E2 s5 p, f
Partial sorting, 偏排序8 _& [: y3 u, w+ F9 f
Partials residuals, 偏残差
. X- @' W) E; {) o$ B$ Y: g, OPattern, 模式
: m5 d: C9 m, E! ]6 N, ]Pearson curves, 皮尔逊曲线
0 c5 F4 x5 H) [0 D, d: UPeeling, 退层
/ W) Y. O, ^' k7 Z7 n7 A. QPercent bar graph, 百分条形图 i* x* S# l/ X1 M, x5 d q
Percentage, 百分比
. S) @! |5 _% I" h* y( I* J. lPercentile, 百分位数
( n6 O( C& Z, z \, j# v1 z8 CPercentile curves, 百分位曲线- M$ G! j! ]8 D0 o/ @) H
Periodicity, 周期性
, i# u5 b$ N! ]& ]* b0 kPermutation, 排列) ]2 X/ ^9 \3 @0 l) P7 X9 j0 ^
P-estimator, P估计量
/ k' a9 M; p; V2 F/ ?3 V+ XPie graph, 饼图. \/ D3 }9 a- O4 P; \- t& X9 i
Pitman estimator, 皮特曼估计量% n4 t" L3 v3 L3 ?' g
Pivot, 枢轴量7 u: ?% C% U1 G+ Q5 H+ I
Planar, 平坦
4 n9 L- `2 ~! H! _- RPlanar assumption, 平面的假设
3 U" m/ D* i0 aPLANCARDS, 生成试验的计划卡
. _+ K5 d( w% f) n: y1 x R9 \: yPoint estimation, 点估计, E3 O h' f, v
Poisson distribution, 泊松分布
/ d. m1 ]/ D( x$ ], s' b, l6 f lPolishing, 平滑+ }$ Z7 d! Y& r+ x% Z/ W
Polled standard deviation, 合并标准差7 n, _% ?4 x5 b8 g2 `7 F$ v8 i4 f$ Y6 @
Polled variance, 合并方差
. c& e h) E# g8 g' f9 _" ?4 yPolygon, 多边图" {7 h' Q2 I$ t; e
Polynomial, 多项式
. \2 j8 L( v' F$ L6 T6 xPolynomial curve, 多项式曲线& w( q9 Z# g0 i5 T# y
Population, 总体- B6 ]3 S* Z% u5 g' ]8 z5 D
Population attributable risk, 人群归因危险度
: {4 C2 V1 {) |6 H% VPositive correlation, 正相关
2 f# b& i! ~* t8 _) kPositively skewed, 正偏
; ~6 k+ D/ h" oPosterior distribution, 后验分布
+ m- I: |0 g$ j/ v* v( t, \Power of a test, 检验效能
0 X5 c" Q, A# h Z4 N+ ^Precision, 精密度
+ f1 h' }' s+ l. ^; ^) m1 N. pPredicted value, 预测值" P A4 ^4 R1 J' T! Q: Z0 V7 A
Preliminary analysis, 预备性分析
# _2 h" I; v: n- B+ D' @, A" RPrincipal component analysis, 主成分分析; I8 `( n j% z8 h/ ]
Prior distribution, 先验分布. k& }- n% T' G% G, c5 H
Prior probability, 先验概率
. t1 i2 n: U% N6 i: ZProbabilistic model, 概率模型
. O% w5 T. W2 J& f* ~, Kprobability, 概率, l2 t) q5 ]" \6 {' Z" P
Probability density, 概率密度
" M: w( M% I9 m$ DProduct moment, 乘积矩/协方差
1 d; G4 g2 u4 M& n$ t( oProfile trace, 截面迹图
- r- f) e. c6 JProportion, 比/构成比
, l' T, S" D+ X5 ZProportion allocation in stratified random sampling, 按比例分层随机抽样$ A; ~( g& c. M2 J5 P& z4 o/ f& w
Proportionate, 成比例' K7 f3 @* ]3 U4 i
Proportionate sub-class numbers, 成比例次级组含量
9 N8 M6 Q9 O" [; U( V+ @) S1 j7 RProspective study, 前瞻性调查
0 @+ b$ u* @* x ~) h! cProximities, 亲近性 5 o/ ^1 y( n, @$ ]0 i8 F0 t
Pseudo F test, 近似F检验
, y8 Z/ m' _! v. Y. d3 d2 J* s9 WPseudo model, 近似模型
0 Q" q1 U3 E% ^- p4 X, [6 FPseudosigma, 伪标准差. {7 f7 k9 ]; g% Z5 v- F
Purposive sampling, 有目的抽样 ?! p6 [ N S- x: H" y
QR decomposition, QR分解
0 ]! }7 y l- QQuadratic approximation, 二次近似
_2 |3 z5 |, B: p; b- i W/ Y# sQualitative classification, 属性分类- `" d1 G' Q! T1 q
Qualitative method, 定性方法
: u M# z; b6 m/ rQuantile-quantile plot, 分位数-分位数图/Q-Q图: j* m' |2 \: @% S
Quantitative analysis, 定量分析0 V# a: t" F3 R# ` T I) C( l
Quartile, 四分位数
: }! u7 S4 P/ L8 {. x8 e; FQuick Cluster, 快速聚类1 ]3 I0 P5 @. b( n
Radix sort, 基数排序* I0 s; K& f k$ S: \8 r2 F
Random allocation, 随机化分组( h% Y# [ j: l9 h- U/ Q4 N& L
Random blocks design, 随机区组设计$ f2 r2 {# S, |5 N0 @4 q
Random event, 随机事件
' H2 U8 j, k U: Y/ ^4 oRandomization, 随机化
$ z7 x) X* D/ w& X$ p6 ^Range, 极差/全距* G: P' s. v, `% \+ U6 M( Z
Rank correlation, 等级相关
! j6 [" [, z, x2 K$ W! vRank sum test, 秩和检验
$ u$ \. R" ?0 G* [Rank test, 秩检验
! m- ?* e8 J3 o4 i- fRanked data, 等级资料) O8 F/ t o# j: J8 I
Rate, 比率
4 Z& S1 }( R! Q+ A9 L% gRatio, 比例4 | p5 v. K+ s# P4 n
Raw data, 原始资料
# J; _: c ]6 ?; E. b. ?7 vRaw residual, 原始残差
/ k8 V) S/ z" c' @( c+ ]! XRayleigh's test, 雷氏检验
3 J0 ]! D+ g! M6 D0 E8 SRayleigh's Z, 雷氏Z值
0 b- T5 B( B% a jReciprocal, 倒数- q7 H- y4 B4 G _
Reciprocal transformation, 倒数变换' T) I Z( f/ K' O8 m1 W
Recording, 记录4 e3 |' X& g4 |- }" Z
Redescending estimators, 回降估计量
9 a- S; |0 Z0 h6 p9 X# k) XReducing dimensions, 降维& |1 N9 _) ~) m# d3 b, t
Re-expression, 重新表达
5 Z" p6 k# P i# lReference set, 标准组1 N& D9 b6 L! ]& J- r- D
Region of acceptance, 接受域
0 @ v2 p: c! S* n, G, oRegression coefficient, 回归系数+ S& l. W' a; S+ B# D
Regression sum of square, 回归平方和
# x( _! V* d$ qRejection point, 拒绝点/ `* \9 j' P% B9 X I
Relative dispersion, 相对离散度
+ `0 V& r+ l- SRelative number, 相对数4 [8 {' g2 H; R" }$ L# p, d1 r
Reliability, 可靠性
; F2 K. g4 P& P w4 z) kReparametrization, 重新设置参数& Y6 T, ^, o% Y/ H8 M/ X* ~
Replication, 重复
2 l) z, E2 F- ~; ~/ s: O/ aReport Summaries, 报告摘要) J5 _' y4 E3 u8 |7 _
Residual sum of square, 剩余平方和) d* u* i' H! z, S+ Z
Resistance, 耐抗性: B \- V, Z6 n
Resistant line, 耐抗线6 X6 X# h$ E: ]5 ? T1 Y2 _& H) f* \
Resistant technique, 耐抗技术
0 V; `4 q1 A2 J/ J$ c) o- O/ M1 f! XR-estimator of location, 位置R估计量
8 [0 c9 R* s- p5 k) y( g) W7 \R-estimator of scale, 尺度R估计量8 E x9 m4 X( X5 K9 X: R$ Z' m
Retrospective study, 回顾性调查
h! ]$ F3 B4 O1 A. C5 ^& J7 ~Ridge trace, 岭迹
) G3 r, d4 D, K; ?, u CRidit analysis, Ridit分析
, C, I. ^) m6 F$ K* VRotation, 旋转
" b! F! b+ c9 `2 @, m* W ZRounding, 舍入 A6 _# u. u# j1 m
Row, 行. D8 F) m7 i+ E7 I1 G
Row effects, 行效应
n4 L5 a* E" g6 GRow factor, 行因素
( d, k; U1 N( d1 r% l, T( mRXC table, RXC表/ |; l" y( |$ a
Sample, 样本- [+ y9 B% i: f0 b1 n6 X# ~
Sample regression coefficient, 样本回归系数 q% E/ p2 R2 ^/ ]% `3 x
Sample size, 样本量
- a" f8 T8 R9 |9 \' @$ xSample standard deviation, 样本标准差! g0 Z2 Z2 T* @, K ]2 ?
Sampling error, 抽样误差
1 ?7 \/ d- R7 t( B( U, c) ?SAS(Statistical analysis system ), SAS统计软件包. i2 x5 L0 K# {6 _: L/ f
Scale, 尺度/量表
7 s3 k) J1 ]2 H# j3 C5 HScatter diagram, 散点图" k2 o6 v' Q" @
Schematic plot, 示意图/简图2 e' Y- n8 a5 X. k& J; _
Score test, 计分检验, q, @8 ]7 n- c$ W6 ?, E2 S
Screening, 筛检
2 z9 V# N( }4 [) n: `SEASON, 季节分析 9 X/ {) L8 s1 o6 G
Second derivative, 二阶导数
# Y- t$ u( L9 [: rSecond principal component, 第二主成分
; {+ X# q. ]4 cSEM (Structural equation modeling), 结构化方程模型
; X0 B7 n- x$ ^, G! s- {Semi-logarithmic graph, 半对数图
/ W# `% a3 Q$ h- a" t7 r, O. {: tSemi-logarithmic paper, 半对数格纸
* E# u: d' F0 b9 e. |Sensitivity curve, 敏感度曲线8 P3 R+ s! l' X" X1 O
Sequential analysis, 贯序分析
+ u- Q$ y" j. g$ X: G' _9 xSequential data set, 顺序数据集& Y* p/ y" ]1 J/ w: R% \( ^- W; t
Sequential design, 贯序设计- n2 {$ Z" p7 j: D5 B/ P
Sequential method, 贯序法
& ^5 j! j$ z) HSequential test, 贯序检验法: Z1 N& |% M6 g7 ~/ M2 X6 m }
Serial tests, 系列试验2 C3 ?" j$ n b; l1 V7 G8 Q
Short-cut method, 简捷法
+ B+ q0 {3 z6 {; tSigmoid curve, S形曲线
' x1 l4 X* U. i& K6 WSign function, 正负号函数, y7 W. F0 Z/ q& [! i
Sign test, 符号检验
' m: o. s) H: T* ]9 S6 T: J& M: gSigned rank, 符号秩: A0 [% l7 T1 U, `
Significance test, 显著性检验
4 J6 X8 i; Q* l6 u9 o6 T4 j( ]Significant figure, 有效数字
1 W$ d( G- F9 n) E' y. _* C6 M* ySimple cluster sampling, 简单整群抽样
, X6 t0 A# I# \! s$ K0 m+ FSimple correlation, 简单相关
; g5 A% a% e. @2 @# ^; ISimple random sampling, 简单随机抽样. f" t2 J+ w% G$ q: u
Simple regression, 简单回归
' R' S( F: v1 J& _8 m6 D1 ysimple table, 简单表
8 `" g; _6 P& A. `6 q$ ZSine estimator, 正弦估计量
1 ] h: P( p, I8 B# V. t5 uSingle-valued estimate, 单值估计8 X% I" R' J4 z; F. ^2 q6 K
Singular matrix, 奇异矩阵8 ?$ ~8 K5 P: l
Skewed distribution, 偏斜分布
6 ^% F7 R, S! rSkewness, 偏度& W+ U* q/ O: | m" @
Slash distribution, 斜线分布
0 R' l- L3 f: N4 V2 KSlope, 斜率' M+ B+ i: v) E: F% j5 {
Smirnov test, 斯米尔诺夫检验+ D, r" A5 C6 C
Source of variation, 变异来源
/ R" |7 D* E& |" E" ^3 m0 {% L3 iSpearman rank correlation, 斯皮尔曼等级相关/ A% P) W7 |3 d9 b5 ?1 M
Specific factor, 特殊因子" a! ^4 O. o3 R
Specific factor variance, 特殊因子方差9 Z, S, y9 Q: f" y, P4 B
Spectra , 频谱" @6 V) Q0 O& }# v: J/ ]; C% J1 f
Spherical distribution, 球型正态分布! c! p. J" U; s" r6 C* }+ ^$ t
Spread, 展布
, @5 t+ g$ S/ K7 N4 G8 v( ESPSS(Statistical package for the social science), SPSS统计软件包( j3 e( D2 J6 `" i( S u/ g
Spurious correlation, 假性相关$ @3 Z) F* c- p7 A
Square root transformation, 平方根变换1 @7 |; b2 e! X/ w) _+ B: I
Stabilizing variance, 稳定方差
_, \- H3 n, ^Standard deviation, 标准差
) p& _% M2 p/ N; s) r& NStandard error, 标准误
' n6 ]1 r7 O5 J5 O7 h. M4 VStandard error of difference, 差别的标准误
$ ]; {4 Y( y7 j |- ~9 c4 W* ~Standard error of estimate, 标准估计误差: Z6 j) o( p- D& m5 j2 O$ n0 o
Standard error of rate, 率的标准误
5 l W" m. O9 a6 Z% T! qStandard normal distribution, 标准正态分布
5 G0 s% ^2 O) n! S" TStandardization, 标准化
3 v& i+ \7 ]1 v) Q. PStarting value, 起始值
_& }) u1 \% I3 q9 D# HStatistic, 统计量
$ E, z3 S1 D# G% I* UStatistical control, 统计控制( j' ]/ M, W+ ]
Statistical graph, 统计图
5 `' l4 V: a, rStatistical inference, 统计推断
F* @" s7 T3 K( `2 ~Statistical table, 统计表+ E1 y0 o' ` X8 ?4 o" H9 H
Steepest descent, 最速下降法5 l3 d) b v% _0 Y5 U6 m: P
Stem and leaf display, 茎叶图
4 q6 U. t1 i! r' M+ U$ aStep factor, 步长因子: M3 r% s+ d. a
Stepwise regression, 逐步回归
& b. |# r- [" i1 O' }% t# Z4 xStorage, 存
- k) u1 G8 Q3 r0 GStrata, 层（复数）6 I- L* p2 f/ ~% F+ T2 e" h
Stratified sampling, 分层抽样+ J1 ], b/ p" u4 M# C
Stratified sampling, 分层抽样/ h# s' u$ ?/ t u6 |
Strength, 强度
# `, s4 X/ ]# SStringency, 严密性
2 i3 E) w% n2 j- Y7 kStructural relationship, 结构关系* s* u9 i- C/ m0 t; |9 ~
Studentized residual, 学生化残差/t化残差
1 v1 M. ^0 _5 s% wSub-class numbers, 次级组含量6 Y5 a% A) o/ |3 N: J
Subdividing, 分割
- ^3 y' P7 C$ x# ~! O' h* sSufficient statistic, 充分统计量9 V* L2 L' ~. S7 L
Sum of products, 积和
: w, o+ y+ `+ V7 xSum of squares, 离差平方和. ^- R3 u& z5 V. g$ x% [7 `) ]9 i+ k
Sum of squares about regression, 回归平方和. M5 g& R( N( f, a( s4 |# V
Sum of squares between groups, 组间平方和% U8 e( F; t3 d0 V2 n. W
Sum of squares of partial regression, 偏回归平方和 C( f0 J0 i& O9 S
Sure event, 必然事件
, V9 r! s! k; T9 XSurvey, 调查! D6 P% O. Q. ]# b0 G1 V
Survival, 生存分析; ~, b3 Z1 n/ H! l1 h: m
Survival rate, 生存率+ D$ U, n6 ?* x+ P
Suspended root gram, 悬吊根图9 ~6 h. Y- D: z
Symmetry, 对称- y5 N* z9 }* [. { q+ T* m9 w
Systematic error, 系统误差
8 ?) E, Y- I, @' cSystematic sampling, 系统抽样4 e2 x5 @3 J: ?. W/ X
Tags, 标签
- Z; b5 V7 _% d* n7 bTail area, 尾部面积
1 y/ h2 E, Z4 m7 ^Tail length, 尾长
# ?# \' p6 F; I, l8 N5 ~0 F6 nTail weight, 尾重
* F7 w( l8 u" z7 f$ XTangent line, 切线
7 D$ }( `! P0 u3 j4 nTarget distribution, 目标分布0 U% O e* D+ M! Z' y; D; i$ b
Taylor series, 泰勒级数+ m4 d* S# [) O; k) p# U" L/ v
Tendency of dispersion, 离散趋势) L( d$ R! c: N0 y A
Testing of hypotheses, 假设检验
8 b: C, M: y7 w8 \$ STheoretical frequency, 理论频数+ m" v% J% f2 g; E7 Z7 }& a; Y+ O
Time series, 时间序列& k1 z4 g9 L1 g
Tolerance interval, 容忍区间
3 c' \: d. p5 x; jTolerance lower limit, 容忍下限
; u& h: O4 o7 o( s9 |, j! N/ oTolerance upper limit, 容忍上限
# v: B! t5 i: d- nTorsion, 扰率
3 `3 Z4 O( R7 xTotal sum of square, 总平方和
: l+ p' |, K0 I4 J; j- QTotal variation, 总变异
/ [9 l# t/ i6 g+ L% JTransformation, 转换/ \& n I: p8 D6 q- G
Treatment, 处理; u3 j8 A! Q* o( U) C+ `
Trend, 趋势- p5 O" }; K& C
Trend of percentage, 百分比趋势" [8 _: e9 Z, o
Trial, 试验, f: E! w& \; A/ g; _1 H
Trial and error method, 试错法
! H u: x" G3 {& b0 uTuning constant, 细调常数! J& B* g8 J0 N# u# _
Two sided test, 双向检验
$ z8 G/ t {+ L* lTwo-stage least squares, 二阶最小平方2 b( |' c+ b6 L$ v8 F
Two-stage sampling, 二阶段抽样. p1 t' z0 U1 ?, R
Two-tailed test, 双侧检验& t- R9 U; H5 B- p3 e) [
Two-way analysis of variance, 双因素方差分析6 ^ \+ G9 a; r3 y8 j1 S& C" c
Two-way table, 双向表( T0 C' l& f- \3 g3 S
Type I error, 一类错误/α错误
" D9 ^: @4 a9 n1 U$ `0 u+ X) vType II error, 二类错误/β错误
& E! A4 l) A& X, ]# W& gUMVU, 方差一致最小无偏估计简称
: Y. r- Q/ {' h& w6 N9 [8 N( S0 W- z0 FUnbiased estimate, 无偏估计9 y% U- y- e2 {6 A( c* D* p
Unconstrained nonlinear regression , 无约束非线性回归2 c: S0 E1 W. T
Unequal subclass number, 不等次级组含量
O- p4 T" E2 W) d) X0 n; K; h% [0 dUngrouped data, 不分组资料* R* d" N' G; Q7 f
Uniform coordinate, 均匀坐标
$ u3 L! B' i1 Z8 S- Z; EUniform distribution, 均匀分布
+ o8 U- C5 {* W4 @Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
8 y$ i2 ?2 u# {Unit, 单元1 s: i( ]7 f& D1 x$ j9 e8 Z
Unordered categories, 无序分类# i' R& h: L' g" t7 X
Upper limit, 上限
8 |9 l) x' P* M+ LUpward rank, 升秩* I2 a2 R- e p
Vague concept, 模糊概念
* @4 ^6 ^, J& t' A( v, @Validity, 有效性
9 A" r6 e& d7 N' vVARCOMP (Variance component estimation), 方差元素估计) y4 ~$ `% }9 r8 \0 `8 v; r
Variability, 变异性" S- n% E4 k0 i8 B7 t3 a; L
Variable, 变量
3 Q& `; G* K( ^; K) b( b" EVariance, 方差7 c3 @$ D/ C, u7 x: ^
Variation, 变异6 K/ @% C0 ?# x' V7 a) j
Varimax orthogonal rotation, 方差最大正交旋转9 `, A" X ]2 c) t. R# A5 g& G
Volume of distribution, 容积
# I e) a, b o% y% Y1 ~: uW test, W检验
2 H. x, T- s9 e" T7 KWeibull distribution, 威布尔分布0 |. o$ w, P9 Z$ o# @9 A7 h% T8 J1 i7 G: L
Weight, 权数6 a: q) m8 c" b' u* _7 L& u3 ]
Weighted Chi-square test, 加权卡方检验/Cochran检验
V$ N: y! C0 D, K1 EWeighted linear regression method, 加权直线回归
; d% S0 z0 j# a K1 K% i$ lWeighted mean, 加权平均数
- I; L1 R0 z, k* ?# e2 `8 S jWeighted mean square, 加权平均方差. b0 |' o5 b% \) f4 u! \
Weighted sum of square, 加权平方和; k7 c/ f- k8 i, I; K" c' X
Weighting coefficient, 权重系数
: a# B' k4 d/ p# W" `Weighting method, 加权法
4 \) I( c2 ]# _ l- wW-estimation, W估计量
6 ~6 g3 h. R" a- x- x5 `W-estimation of location, 位置W估计量
+ H6 }0 [9 K8 v% n% s% NWidth, 宽度" r& c# u5 ]2 _9 F* V
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验' G ?2 c* _! i; p' n! K4 q4 U7 `8 V
Wild point, 野点/狂点
9 o1 f( p, b r1 c/ ^! z' P! aWild value, 野值/狂值0 P5 n3 m) S. M) W
Winsorized mean, 缩尾均值
4 V' Z# J3 Q* `. a# N% m, JWithdraw, 失访 9 t; f7 C5 @; Q0 a& @) C' l
Youden's index, 尤登指数
: K! j8 d( P& A- f! IZ test, Z检验8 R, G9 E" f6 ]7 A! d9 r: W8 ^, G
Zero correlation, 零相关
3 {. c0 v+ e% d$ NZ-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看，没有账号？注册会员
x
|
|李越老师直播间|清流社工网
( 苏ICP备19044186号-1 )
发表于 2009-1-6 22:05
